What Does Facebook Know About You?

Wired called Mark Zuckerberg’s hearings “Silicon Valley’s Ultimate Debut”

For many of us in the tech industry, Mark Zuckerberg’s congressional hearings were painful to watch. But in reality, we’re the ones living in a “tech echo-chamber,” and it was evident in the questions that were being asked by U.S. Senators.

The most memorable one came from Sen. Orrin Hatch, the 84-year-old Republican from Utah:

“If [a version of Facebook will always be free], how do you sustain a business model in which users don’t pay for your service?”

“Senator, we run ads.”

While the rest of us sat here and smirked, this made it clear that the 44 senators from the U.S. Senate Judiciary and Senate Commerce, Science, and Transportation committees had no idea how Facebook works, no less, the magnitude of the data scandal at hand.

Following up on my last post, it’s worth it to take a deeper dive into exactly how consumer apps make money. Some of the most successful apps use the “freemium” model where the app is free to download but offers options for upgrading to the full product or unlocking additional features through in-app purchases. To give you some perspective, according to App Annie, freemium apps account for 95% of Apple App Store revenue and 98% of Google Play Store revenue.

So, how do freemium apps make that much money?

First, it’s important to understand that most of the revenue generated through freemium apps come from the top 1–3% of users (app developers call these users *whales*). With free apps helping to attract a large number of downloads, developers can then hone in on the in-app behavior of users to identify different cohorts of users. Companies like Gondola.io, for example, can analyze a player’s progress through a game and change prices based on his or her habits to yield higher engagement and in-app purchases for developers.

Apps that offer no paid services have significantly different revenue streams, yet their business models do not differ that much from their freemium counterparts. In fact, free services like social media platforms benefit even more from a lot of the freemium apps’ hook-and-reward engagement tactics because they can make money off of all users. Rather than looking to zero in on those willing to spend and then getting them to engage more with the app, companies like Facebook profit from getting anybody to use their platform since usage translates to more shared data, which can be turned around and sold to advertisers.

Before we can get to the bottom of how companies use our data, it’s important first to understand what these companies are allowed to collect.

Facebook says it only collects information we are generally fine with sharing: name, email, age, sex, relationship status, education, work history, interests, location, facial recognition, and friends list. But that isn’t all of it, and it’s definitely not what’s really intrusive or most valuable to advertisers.

The data we share with Facebook, coupled with data they have on our use of their platform — what we type, click, or look at — gives data scientists the tools they need to put us into cohorts for which advertisers will pay top dollar. Though this information isn’t public, insights gleaned from data science can give us a good idea as to what that might resemble.

For example, data selfie, a Chrome extension developed by an ex-Facebook employee, lets you to track your own usage of Facebook and learn what the platform might be gathering about you.

Though I haven’t been using the extension for more than a few days, here is an example of how data scientists at Facebook could make particilar assumptions about my shopping habits, despite the fact that I have zero to no interaction with clothing brands on Facebook:

Information like this is much more valuable to advertisers than the boilerplate information Facebook says they collect, such as age, gender, and relationship status. In my case, for example, Facebook could share this data with REI and convince them to shell out more money to reach me, leaving the H&M’s and Zara’s of the world to skip me and focus their resources converting users who feel more positively about their brands.

Providing advertisers with the confidence of higher ROI allows Facebook to market more expensive ad solutions to these companies — long gone are the days of every user seeing the same three banner ads when they log into a social media app. Instead, we now see sponsored posts by paid influencers on Instagram, high production value video ads on our Facebook feeds, and sponsored content that discreetly makes brands appealing to specific cohorts.

So, how does one quantify the value of a consumer data?

To start, we know it must be high, given the substantial increase social media and branding budgets over the past several years. Getting more specific, this post from Shopify (https://www.shopify.com/blog/customer-lifetime-value), helps us understand how to calculate a consumer’s lifetime value. This numbers-based approach hinges on two things:

1) Collect consumer data at an individual level. Consumer data such as average order volume and purchase frequency

2) Target most valuable groups. This is the part where social media comes in. A lot of the advertisement on Facebook and other platforms is done before a customer ever shops for the brand online, so how do you know to target them? The answer is by taking data about the people who have already shopped with you, and understand the similarities between them. Once you’ve done this, you can assume that others who share these similarities will also be interested in what you have to sell. The more data that is collected, the more ways there are to segment users and get to that high-spending cohort without wasting resources on the rest.

In short, the data being collected by social media platforms is used in ways that allow them and advertisers to work together to bucket us into segments and create more efficient ways to market to us. These segments can be based on similarities in simple things such as age and hometown, but are often more effective when they’re formed off of more intimate details of our personalities.

To get to the data that allows platforms like Facebook to know these things about us, they have to keep us engaged and on the platform.

Simply put, our time spent on their site helps generate more data, which allows them to build eerily accurate profiles of our likes, aspirations, interests, and behaviors, which entices advertisers to spend more for high returns.

So, if the driver in this economy boils down to users creating IP with their time, why can’t they get their fair share of the rewards?

by Zev Bimstein, Growth and Strategy for Siglo